Synchronous Generator System Research Articles

Comparative study of magnetic energy storage control techniques for stabilizing wind farm integrated system under different conditions

The Superconducting Magnetic Energy Storage (SMES) device is gaining significance in utility applications, as it can handle high power values with a fast rate of exchanging energy at high efficiency. The large-scale invasion of renewable energy systems into grid give rise to many integration issues. This SMES can handle these issues due to its various features. In this study the role of SMES in tackling stability issues due to presence of wind generation farms is investigated. The Doubly Fed Induction Generators (DFIG) based wind farms are most popular due to their distinctive advantages. Their intermittent output power and sensitivity to the grid disturbances gives rise to stability issues. These problems require innovative and advanced control strategies. Here coupling of SMES with Static Compensator (STATCOM) (STAT-SMES) has been suggested for boosting the transient stability of the hybrid large-scale DFIG and Synchronous Generator (SG) system. For investigation different faults and fast speed wind variation are considered. This coupled controller can compensate the real and reactive powers along with fast damping of oscillations under test conditions of entire system. The chopper link of SMES is controlled using Fuzzy based intelligent system and Proportional Integral (PI) controller. The connection of SMES to STATCOM shows better damping and improvement in all variables. The comparative study among Fuzzy based STAT-SMES, PI based STAT-SMES, only STATCOM, and without any controller is performed using MATLAB/Simulink. The simulation outcomes indicate that proposed Fuzzy based controller is better than other control systems in different test conditions.

Dynamic Frequency Performance Analysis and Improvement for Parallel VSG Systems Considering Virtual Inertia and Damping Coefficient

Parallel virtual synchronous generator (VSG) systems are emerging as an attractive solution for inertia support and frequency stability enhancement of the power grid. However, the dynamic frequency characteristic is more complicated due to the coupled interaction of line impedance, virtual inertia, and damping coefficient in parallel VSG systems. The problems for frequency stability, dynamic performance, and frequency/power oscillation have raised much more attention. In this article, a systematic analysis of the influence of virtual inertia and damping coefficient on the dynamic frequency characteristic among parallel VSG systems was presented, and a quantitative assessment for dynamic frequency performance based on the 2-norm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\boldsymbol {\mathcal{ H}}_{2}$ </tex-math></inline-formula> was proposed. Furthermore, a coordinated control for virtual inertia and damping was proposed to improve frequency stability and achieve a better dynamic performance of parallel VSG systems. The effectiveness and superiority of the proposed method were verified by simulation and experimental results.

Modeling of Direct-Drive Permanent Magnet Synchronous Wind Power Generation System Considering the Power System Analysis in Multi-Timescales

The dynamics of wind power generation cannot be neglected in the modern power system and could have a great impact on the system dynamics, even raising the risk of a blackout. Because of this, power system simulation has to include the model of wind power generation. However, due to the high order of the full model of the wind power generator, it is impossible to model them in detail in the use of the power system dynamic simulation considering the thousands of wind generators in the grid. In this context, a simplified model is normally used with the trade-off in lower accuracy. As a direct-drive permanent magnet synchronous wind power generation system (D-PMSG) would take up a certain occupation in the modern power system, a proper D-PMSG simplified model is needed in the power system simulation. For a different research purpose in a different timescale, a different complexity of the model can be used to maximize the accuracy, in the meantime speeding up the simulation. This paper proposes a set of simplified models of the direct-drive permanent magnet synchronous wind power generation system (D-PMSG) and classifies them according to the timescale of the dynamics and the use cases, i.e., faults (transient stability analysis), system contingencies (voltage and frequency stability analysis) and wind speed variations (energy transformation). The accuracy of the proposed simplified models is verified by comparing them with the detailed D-PMSG electromagnetic transient mode in Matlab/Simulink, and their use case of the power system simulation is validated based on the case study of the IEEE 39-bus system considering the above scenarios.

Deployment and performance measurement of renewable energy based permanent magnet synchronous generator system

Permanent magnet synchronous generator (PMSG) is one of the promising solutions for large power generation systems due to its many advantages. The off-grid and micro/pico-hydro power stations are located near to the loads and equipped with constant speed/power turbine sources. In this paper, an attempt is made to design, develop, and deploy a three-phase PMSG generating system for the small scale off-grid dedicated load applications. In this experimental study, a constant speed source, which is an emulation of a micro/pico-hydro turbine is used as the prime mover to the generator. The prime mover is mechanically coupled to the rotor of the generator and which is controlled by an AC driver to make the PMSG run at synchronous speed for all the time of the experiment to generate the required voltage and frequency. The performance of the three-phase PMSG is measured and analyzed so that the proposed system obeys the good power quality for the pre-defined various maximum loading conditions.

Intelligent approach on sensorless control of permanent magnet synchronous generator

In this paper, a standalone permanent magnet synchronous generator (PMSG) system is designed to generate power at maximum power point (MPP). The variable speed operation of wind energy conversion system consists of PMSG, controlled rectifier and voltage source inverter co to the load. Proportional integral (PI), sliding mode (SM), and feed forward neural network (FFNN) control strategies are applied in field oriented control (FOC) at generator side converter. A comparative study on power generated at maximum power point (MPP) is done with these controllers using simulation. Hill climb search (HCS) method is applied to attain MPP. Load side inverter control strategy involves the PI and SM controllers in order to maintain the unity power factor and to control the active and reactive power for nonlinear load. The control strategies are modelled and simulated with MATLAB/Simulink. The effectiveness of proposed control method is demonstrated using simulation results.

Study of shoot-through control pulse generation for a Z-source converter with wind turbine energy system

In this paper, there is a discussion about different modulation schemes for a dc-to-ac ZSC, also named Z-source inverter (ZSI), for triggering the main switches of three-phase legs or poles of an inverter. A prototype of an 8.5-kilowatt wind turbine with a 5.8-kilowatt Permanent Magnet Synchronous Generator (PMSG) system employed with voltage-controlled ZSI is implemented in this paper. For voltage control of load side of a wind turbine generation system (WTGS), a Proportional Integral (PI) controller is used. Three types of PWM schemes namely simple boost pulse width modulation (SB-PWM), third harmonic injection boost control (THIBC-PWM) and the space vector pulse width modulation (SV-PWM) techniques are compared on the basis of total harmonic distortion of the output ac-waveform of the Z-source Converter (ZSC) to find out that, which modulation technique is the best fit for a ZSI integrated with WTGS. The pros and cons of these techniques are compared in terms of line-voltage harmonics, phase-voltage harmonics, phase-current harmonics and switching stress of switches with detailed simulation results. These different modulation techniques are implemented on the MATLAB-Simulink domain. From Total Harmonic Distortion (THD) analysis, simple boost control technique is found to be the most appropriate shoot-through control technique for a ZSI in collaboration with WTGS.

Enhancing Diesel Generator Fuel Efficiency by Operating in Optimum Variable-Speed Combined with Vienna Converter

Diesel engine generators are commonly used in refinery systems to provide electrical power. The engines are generally Constant Speed Diesel Wound Rotor Synchronous Generator (CSD-WRSG) type and are operated in parallel with ones. In this study, a Variable Speed Diesel Wound Rotor Synchronous Generator (VSD-WRSG) system is proposed, combined with additional AC-to-DC and DC-to-AC converters, in order to meet the low load condition and save the fuel. The Diesel Generator's current rotation, which is set at a constant speed, is then changed to the optimum speed. It varies depending on the load demand. The electrical frequency is controlled through the converters. This research focuses on a single diesel generator with a capacity of 880 kW for supplying 343 kW average load demand. The AC-to-DC converter employs a Vienna Rectifier with hysteresis control. In order to enable smooth power transmission during load changes, a DC-to-AC converter is used with a Virtual Synchronous Generator control method. All the simulations are completed using MatLab/Simulink. The simulation results indicate that the proposed model is effective. When daily load data is employed, the VSD-WRSG system can save up to 5.3% or 121 liters of fuel per day if compared to the CSD-WRSG system.

Starting Control of Free Piston Stirling Linear Generator System Based on FOC

Aiming at the problem of poor system dynamic performance caused by low parameter matching in the coordinated control of Stirling engine and linear generator in the starting stage control of free piston Stirling linear generator system, a joint control method of free piston Stirling permanent magnet synchronous linear generator system based on field orientation control is proposed, based on the theoretical derivation of the mathematical model of the system and the principle of controller parameters setting, the simulation experiments of the system starting stage under several Stirling engine working conditions are carried out under simulation. The experimental results show that the stability and rapidity of the system are improved, and the dynamic response speed of generator parameters under different working conditions is accelerated, what fully verifies the correctness and effectiveness of the method. It provides an effective way to improve the control performance of the system and stabilize the power generation operation.

Operation Method of Energy Storage System Replacing Governor for Frequency Regulation of Synchronous Generator without Reserve

This paper proposes an operation methodology for interfacing synchronous generator and energy storage system (ESS) by replacing conventional governor. This research introduces energy management scheme with droop control method for frequency regulation in coordination with synchronous generator. For frequency regulation, generator can take advantage of the ESS instead of the governor, with its relatively fast characteristics, leading to less frequent deviation of synchronous generator. For the verification, we simulate a network reduction model from real Korean network data, based on the case studies using PSCAD/EMTDC software.

Reinforcement Learning-Based Adaptive Optimal Fuzzy MPPT Control for Variable Speed Wind Turbine

A reinforcement learning-based adaptive optimal fuzzy controller is proposed for maximum power point tracking (MPPT) control of a variable-speed permanent magnet synchronous generator-based wind energy generation system. The algorithm consists of a critic, an adaptive optimal fuzzy controller, and an adaptive optimal fuzzy estimator. The critic is built based on an adaptive neuro-fuzzy inference system (ANFIS) network instead of the neural network as normal to reduce the computation. The error between the system output and the estimator output is used as the input of the critic. In addition, the critic is used to calculate the update law for the parameters of the adaptive optimal fuzzy controller and adaptive optimal fuzzy estimator based on minimizing the input error function. Moreover, the proposed control scheme is output feedback instead of state feedback, which does not require a system model as well as system parameters, so the system is robust to uncertainties and external disturbances. Besides, the stabilization proof is accomplished by using the Lyapunov stability theorem for the closed-loop system and the convergence of the update law. Finally, the effectiveness of the proposed reinforcement learning-based adaptive optimal fuzzy control scheme is verified through simulation with various scenarios such as step wind speed, random wind speed, and system parameter variations. Also, the comparisons with other control schemes in the state-of-art (neural network reinforcement learning based adaptive optimal fuzzy controller, PI controller) are executed to demonstrate the advantages of the proposed control scheme.

A Dual Adaptive Inertia and Damping Control Strategy of ANFIS-VSG for Direct-drive Permanent Magnet Synchronous Wind Generator Systems

A Dual Adaptive Inertia and Damping Control Strategy of ANFIS-VSG for Direct-drive Permanent Magnet Synchronous Wind Generator Systems

Three-level Vienna Rectifier with a Brushless and Permanent Magnetless Generator for Wind Energy Conversion Systems

Abstract This paper proposes a system design and control technique for a newly developed brushless and permanent magnetless synchronous generator-based variable-speed wind energy generation system, transferring power to a constant voltage dc grid via a three-level Vienna rectifier (VR). The recently established generator named Brushless Induction excited Synchronous Generator (BINSYG) is a wound field synchronous generator (WFSG), whose excitation is developed by controlling an Induction Machine fitted to the same machine structure and sharing the same magnetic core. A new controller is proposed that ensures the stable operation of BINSYG for a wide variation of shaft speeds. VR achieves sinusoidal input current and can control the power factor at its input, which is particularly suitable for wind energy applications. The top and bottom capacitor voltages of the VR are balanced using redundant switching combinations. The system with its proposed control algorithm is modelled in MATLAB/Simulink for a 5 kW rated BINSYG feeding power to a 750 V dc grid. The steady-state and dynamic state simulation results are presented and the controller performance is verified for a wide range of wind speeds. Further, real-time results using the OPAL-RT testbed are presented for the same system to verify the effectiveness of the overall control strategy.

Rapid Detection of Small Faults and Oscillations in Synchronous Generator Systems Using GMDH Neural Networks and High-Gain Observers

This paper presents a robust and efficient fault detection and diagnosis framework for handling small faults and oscillations in synchronous generator (SG) systems. The proposed framework utilizes the Brunovsky form representation of nonlinear systems to mathematically formulate the fault detection problem. A differential flatness model of SG systems is provided to meet the conditions of the Brunovsky form representation. A combination of high-gain observer and group method of data handling neural network is employed to estimate the trajectory of the system and to learn/approximate the fault- and uncertainty-associated functions. The fault detection mechanism is developed based on the output residual generation and monitoring so that any unfavorable oscillation and/or fault occurrence can be detected rapidly. Accordingly, an average L1-norm criterion is proposed for rapid decision making in faulty situations. The performance of the proposed framework is investigated for two benchmark scenarios which are actuation fault and fault impact on system dynamics. The simulation results demonstrate the capacity and effectiveness of the proposed solution for rapid fault detection and diagnosis in SG systems in practice, and thus enhancing service maintenance, protection, and life cycle of SGs.

Fault Ride Through Capability Enhancement of Permanent Magnet Synchronous Generator-based Wind Energy Conversion System

With the speedy increase of wind energy in electric networks, many important issues could emerge, where the most important matter is to maintain the connection of wind generators during fault conditions. With different faults in the electrical network, the voltage at the point of common coupling (PCC) decreases causing unwanted transients in the stator currents. This results in substantially increased fluctuations in the DC-link voltage (Vdc). To avoid this negative impact, it is a must to maintain the capability of wind generators to continue linked to the network during faults, which is depicted as low voltage ride through (LVRT) capability. This paper investigates the LVRT enhancement by two techniques, the first is based on Braking Chopper (BC) and the second method is based on electrical double-layer capacitors (EDLC), or Supercapacitor Energy Storage System (SCESS), under abnormal conditions. The full model of the permanent magnet synchronous generator (PMSG) system and FRT technique are performed in MATLAB/Simulink platform. As a consequence of the findings, both the BC and SCESS are capable to provide satisfactory performance with superior FRT capability for the SCESS compared to the BC.

Pole Location and Input Constrained Robust Fuzzy Control for T-S Fuzzy Models Subject to Passivity and Variance Requirements

In this paper, a robust fuzzy controller for stochastic nonlinear systems subject to multiple performance constraints is discussed. To solve the problem of stochastic behaviors in nonlinear systems, the covariance control theory and passive control theory are applied based on the concept of energy. Additionally, the pole placement method is considered for the better transient behaviors of the system responses. However, it is known that the control inputs and maximum overshoot of the system responses may become bigger at the same time when the settling time or converge rate of the system is required to be faster. Due to this reason, the input constraint is also considered in the fuzzy controller design method to limit the value of the control gain. Moreover, an effective robust control method is applied to deal with the perturbation of the nonlinear systems. Based on the above performance constraints, the sufficient conditions can be obtained to achieve the stability in the sense of mean square and the multi-performance requirements. Finally, simulation results of the nonlinear synchronous generator system are presented to verify the feasibility and efficiency of the proposed control method.

QoS aware joint observer and networked PI/PID controller design using LMIs under specified rate of packet dropouts

This paper develops a novel formulation for quality of service (QoS) aware networked observer and PI/PID controller design in the presence of specified rate of random packet dropouts. We here derive the stability conditions for the controller and observer gains using asynchronous dynamical system (ADS) formulation of the networked control system (NCS) in discrete time which yields a set of linear matrix inequalities (LMIs). The control design has been validated on two test-bench energy systems viz. battery with DC/DC converter and synchronous generator with power system stabilizer. Numerical simulations report the joint observer and controller's performance in the presence of random packet drops within output feedback control scheme using PI/PID controllers and employing state estimation for the battery and synchronous generator systems. The major numerical challenge includes handling nonconvex constraints in LMIs and stabilizing the observer-based controller with specified rate of packet dropouts. Monte Carlo simulations are provided to compare the uncertain state trajectories, state estimation errors and control efforts under different probability of packet dropouts for the two test-bench energy systems.

3-D Vector-Based Model Predictive Current Control for Open-End Winding PMSG System With Zero-Sequence Current Suppression

In this article, 3-D vector-based model predictive current control (MPCC) for the open-end winding permanent magnet synchronous generator (OEW-PMSG) system driven by a dual inverter with a common dc bus is proposed to suppress the zero-sequence current. First, the 3-D voltage vector distribution of this system is analyzed and their zero-sequence voltages are investigated. Then, in order to reduce the computation burden of prediction control caused by vector enumeration, an improved current prediction control is developed, in which candidate voltage vectors for the dual inverter are determined according to the position of the zero-sequence reference voltage vector and the sector location of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\alpha \beta $ </tex-math></inline-formula> -axis reference voltage vector. Moreover, to further improve the steady-state control performance of the whole generation system, a separate vector-selection method for the dual inverter is proposed. In this method, the first inverter applies one voltage vector in a control period and the voltage vector of the second inverter is synthesized by two vectors and selected in 3-D space. Finally, experiments are carried out to validate proposed methods, and the comparison experiments indicate that the proposed method has better control performance compared to conventional methods.

Coordinated Control Strategy of Virtual Synchronous Generator Based on Adaptive Moment of Inertia and Virtual Impedance

The application of virtual synchronous generators in the power system eases the pressure on the grid caused by penetration of lots of power electronic devices, but worsens the dynamic frequency stability of the grid. Meanwhile, in order to solve the problem of power coupling in low-voltage micro-grid systems, most measures introduced virtual impedance technology to adjust the equivalent output impedance of the system. Therefore, most studies have adopted the adaptive control strategy of the moment of inertia, to improve the dynamic frequency adjustment of the grid. However, it will cause the frequency response speed reduction problem. In order to deal with the contradiction between the moment of inertia and frequency response speed, the voltage phasor relationship of the micro-source - grid system under signal disturbance in the introduction of virtual impedance is analyzed. Then an adaptive virtual impedance control strategy is proposed to accelerate the active power adjustment process of the virtual synchronous generator system, which helps to complete the first frequency modulation and improve the inertia adjustment ability. Finally, combining these two control strategies, a coordinated adaptive moment of inertia and virtual impedance control strategy is proposed. From the perspective of the moment of inertia and virtual impedance, the proposed method fully exploits the control advantages of the virtual synchronous generator system and achieves the purpose of adjusting the inertia of the virtual synchronous generator system while considering the acceleration of the frequency response speed. The comprehensive simulation results verify the feasibility and effectiveness of the proposed method.

Variable-Speed Hydropower Generation: System Modeling, Optimal Control, and Experimental Validation

The variable-speed hydropower generation technology of small hydropower plants has great potential because of abundant water resources and the low overall efficiency of the traditional constant speed plants. In this article, we investigate a converter-fed synchronous generator system capable of variable-speed operation (VSO) in the full power range. First, the hydraulic turbine, permanent magnet synchronous generator, and power electronic converter in the system are modeled, respectively. Next, based on the system model, a three-layer control system is proposed to realize the multiobjective control. To automatically track the optimal speed under different inflow rates, a modified “perturb and observe” algorithm is proposed, which is easy to implement and able to track the maximum power point quickly and accurately compared with the classical method. In addition, the proposed system is used to reconstruct one of the two parallel hydropower sets with the same hydrological conditions. And the performance tests and comparative experiments between the fixed-speed operation and VSO sets were extensively performed. It shows that a considerable increase in energy production is achieved in the VSO set.

Application of Reference Voltage Control Method of the Generator Using a Neural Network in Variable Speed Synchronous Generation System of DC Distribution for Ships

In the case of DC power distribution-based variable speed engine synchronous generators, if the output reference voltage is kept constant regardless of the generator engine operating speed, it may cause damage to the internal device and windings of the generator due to over-flux or over-excitation. The purpose of this study is to adjust the generator reference voltage according to the engine speed change in the DC distribution system with the variable speed engine synchronous generator. A method of controlling the generator reference voltage according to the speed was applied by adjusting the value of the variable resistance input to the external terminal of the automatic voltage regulator using a neural network controller. The learning data of the neural network was measured through an experiment, and the input pattern was set as the rotational speed of the generator engine, and the output pattern was set as the input current of the potentiometer. Using the measured input/output pattern of the neural network, the error backpropagation learning algorithm was applied to derive the optimum connection weight to be applied to the controller. For the test, the variable speed operation range of the generator engine was set to 1100–1800 rpm, and the input current value of the potentiometer according to the speed increase or decrease within the operation range and the output of the voltage output from the actual generator were checked. As a result of neural network control, it was possible to confirm the result that the input current value of the potentiometer accurately reached the target value 4–20 mA at the point where the initial speed change occurred. It was confirmed that the reference voltage was also normally output in the target range of 250–440 V.